The Artificial Intelligence in Medicine (AIM) PhD track, newly developed by the Department of Biomedical Informatics (DBMI) at Harvard Medical School, will enable future academic, clinical, industry, and government leaders to rapidly transform patient care, improve health equity and outcomes, and accelerate precision medicine by creating new AI technologies that reason across massive-scale biomedical data and knowledge.
Students will learn from and work alongside leading AI researchers, including Isaac “Zak” Kohane, Arjun Manrai, Chirag Patel, Pranav Rajpurkar, Kun-Hsing Yu, Marinka Zitnik, Maha Farhat, and Tianxi Cai. Together, they will build AI tools that cut across the latest modalities in fields such as generative language models, graph neural networks, and computer vision, incorporating diverse data types to improve clinical decision-making and biomedical research.
In addition to coursework in state-of-the-art medical AI, students will enrich their understanding of the challenges and opportunities for AI as applied to the clinical care system by performing hospital rotations alongside medical students and other Harvard and MIT PhD trainees, through a collaboration with the Harvard–MIT Program in Health Sciences and Technology.
AIM students will gain an unparalleled understanding and appreciation for how their research will tangibly impact health care and patient well-being. This approach is designed to enhance innovation between fields such as statistics, computer science, bioinformatics, artificial intelligence, epidemiology, and clinical medicine in order to effect the changes urgently needed in healthcare.
An innovative aspect of the AI in Medicine track is its co-mentorship model, in which students will select one methodological mentor and one hospital-based clinical scientist mentor. The goal is to encourage significant interdisciplinary alignment among students, DBMI faculty, and HMS-affiliated clinical scientists, thereby increasing the translational impact of the student’s research.